A wireless transmitting method includes calculating a beamforming channel matrix which is a channel matrix generated at a time when a transmitting apparatus applies a beamforming matrix to a data signal and transmits the data signal to receiving apparatuses, selecting a parameter to be used while transmitting the data signal based on the beamforming channel matrix and noise information fed back from the receiving apparatuses, and transmitting the data signal by using the selected parameter.
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12. A transmitting method comprising:
calculating a beamforming channel matrix, which is a channel matrix generated at a time when a transmitting apparatus applies a beamforming matrix to a data signal and transmits the data signal to receiving apparatuses;
selecting a parameter that is used while transmitting the data signal based on an error rate estimated by using the beamforming channel matrix and noise information fed back from the receiving apparatuses; and
transmitting the data signal by using the selected parameter.
16. A receiving method comprising:
receiving a pilot signal to which a beamforming matrix is applied from a transmitting apparatus;
estimating a beamforming channel matrix which is a channel matrix generated at a time when the transmitting apparatus applies the beamforming matrix to the pilot signal and then transmits the pilot signal to a receiving apparatus;
selecting a parameter to be used while transmitting a data signal based on an error rate estimated by using the beamforming channel matrix and noise information included in the pilot signal; and
transmitting the selected parameter to the transmitting apparatus.
1. A transmitting apparatus comprising:
a beamforming channel matrix calculator, which calculates a beamforming channel matrix, which is a channel matrix generated at a time when the transmitting apparatus applies a beamforming matrix to a data signal, and then transmits the data signal to receiving apparatuses;
a transmission parameter selector, which selects a parameter that is used while the data signal is transmitted by the transmitting apparatus, based on an error rate estimated by using the beamforming channel matrix and noise information fed back from the receiving apparatuses; and
a transmitter, which transmits the data signal by using the selected parameter.
20. A non-transitory computer readable medium having computer readable code to implement a method of receiving, the method comprising:
receiving a pilot signal to which a beamforming matrix is applied from a transmitting apparatus;
estimating a beamforming channel matrix which is a channel matrix generated at a time when the transmitting apparatus applies the beamforming matrix to the pilot signal and then transmits the pilot signal to a receiving apparatus;
selecting a parameter to be used while transmitting a data signal based on an error rate estimated by using the beamforming channel matrix and noise information included in the pilot signal; and
transmitting the selected parameter to the transmitting apparatus.
8. A receiving apparatus, comprising:
a beamforming channel estimator, which receives a pilot signal to which a beamforming matrix has been applied, from a transmitting apparatus, and estimates a beamforming channel matrix, which is a channel matrix generated at a time when the transmitting apparatus applies the beamforming matrix to the pilot signal and transmits the pilot signal to the receiving apparatus, from the pilot signal;
a transmission parameter selector, which selects a parameter to be used while transmitting a data signal based on an error rate estimated by using the beamforming channel matrix and noise information included in the pilot signal; and
a transmitter, which transmits the selected parameter to the transmitting apparatus.
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This application claims the benefit of Japanese Patent Application No. 2007-161543, filed Jun. 19, 2007, in the Japan Patent Office, and Korean Patent Application No. 2007-129106, filed Dec. 12, 2007, in the Korean Intellectual Property Office, the disclosures of which are incorporated herein in their entireties by reference.
1. Field of the Invention
Aspects of the present invention relate to a wireless communication apparatus and method using a multiple-input and multiple-output (MIMO) method.
2. Description of the Related Art
A multiple-input and multiple-output (MIMO) method is a technology that is used to accelerate communication speed between wireless apparatuses. The MIMO method inputs and outputs a signal by using a plurality of antennas. A characteristic of the MIMO method is that plural pieces of transmission data can be simultaneously transmitted by using different antennas. Accordingly, as the number of channels that can simultaneously transmit data increases, the amount of information that can be transmitted per unit time also increases according to an increased number of channels. Also, according to the MIMO method, the number of frequency bands that are occupied does not increase as the communication speed increases.
However, since a plurality of modulating signals having a carrier wave component of the same frequency is simultaneously transmitted, a receiving apparatus requires a device to separate mixed modulating signals. Accordingly, the receiving apparatus estimates a channel matrix that shows a transmission characteristic of a wireless transmission path, and separates a transmission signal corresponding to each sub-stream transmitted from a transmitting apparatus, from a reception signal based on the estimated channel matrix. The channel matrix is estimated by using a pilot signal, or the like. The pilot signal is a signal already known by the receiving and transmitting apparatuses, and the receiving and transmitting apparatuses can estimate the channel matrix by transmitting and receiving the pilot signal.
However, specific research is required to realize a high precision transmission signal corresponding to a sub-stream by sufficiently removing effects of noise added in the transmission path and interference generated between sub-streams.
One or more embodiments of the present invention provide a wireless communication apparatus and method using beamforming to maintain stable throughput in a multi user multiple-input and multiple-output (MIMO) system.
Additional aspects and/or advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
According to an aspect of the present invention, a transmitting apparatus includes a beamforming channel matrix calculator, which calculates a beamforming channel matrix, which is a channel matrix generated at a time when the transmitting apparatus applies a beamforming matrix to a data signal, and then transmits the data signal to receiving apparatuses; a transmission parameter selector, which selects a parameter that is used while the data signal is transmitted by the transmitting apparatus, based on the beamforming channel matrix and noise information fed back from the receiving apparatuses; and a transmitter, which transmits the data signal by using the selected parameter.
According to another aspect of the present invention, a receiving apparatus includes a beamforming channel estimator, which receives a pilot signal to which a beamforming matrix has been applied, from a transmitting apparatus, and estimates a beamforming channel matrix, which is a channel matrix generated at a time when the transmitting apparatus applies the beamforming matrix to the pilot signal and then transmits the pilot signal to the receiving apparatus, from the pilot signal; a transmission parameter selector, which selects a parameter to be used while transmitting a data signal based on the beamforming channel matrix and noise information included in the pilot signal; and a transmitter, which transmits the selected parameter to the transmitting apparatus.
According to another aspect of the present invention, a transmitting method includes calculating a beamforming channel matrix, which is a channel matrix generated at a time when a transmitting apparatus applies a beamforming matrix to a data signal and transmits the data signal to receiving apparatuses; selecting a parameter that is used while transmitting the data signal based on the beamforming channel matrix and noise information fed back from the receiving apparatuses; and transmitting the data signal by using the selected parameter.
According to another aspect of the present invention, a receiving method includes receiving a pilot signal to which a beamforming matrix is applied from a transmitting apparatus, estimating a beamforming channel matrix which is a channel matrix generated at a time when the transmitting apparatus applies the beamforming matrix to the pilot signal and then transmits the pilot signal to a receiving apparatus; selecting a parameter to be used while transmitting a data signal based on the beamforming channel matrix and noise information included in the pilot signal; and transmitting the selected parameter to the transmitting apparatus.
According to another aspect of the present invention, a computer readable medium having computer readable code implements a method of receiving data, the method including: receiving a pilot signal to which a beamforming matrix is applied from a transmitting apparatus, estimating a beamforming channel matrix which is a channel matrix generated at a time when the transmitting apparatus applies the beamforming matrix to the pilot signal and then transmits the pilot signal to a receiving apparatus; selecting a parameter to be used while transmitting a data signal based on the beamforming channel matrix and noise information included in the pilot signal; and transmitting the selected parameter to the transmitting apparatus.
These and/or other aspects and advantages of the invention will become apparent and more readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
Reference will now be made in detail to the present embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the like elements throughout. The embodiments are described below in order to explain the present invention by referring to the figures.
Each of the receiving apparatuses 40 includes a channel estimator 44 and antennas 42. The channel estimator 44 estimates a sub-channel matrix, which indicates a transmission characteristic of a sub-channel between the transmitting apparatus 10 and the receiving apparatus 40. The sub-channel exists in each receiving apparatus 40 that communicates with the transmitting apparatus 10. A channel matrix shows a transmission characteristic of a channel in a matrix, and a sub-channel matrix is a channel matrix corresponding to a combination of a transmission antenna and a reception antenna. For example, the channel estimator 44 may estimate a sub-channel matrix by using a pilot signal added to a transmission signal transmitted from the transmitting apparatus 10, although it is understood that the channel estimator 44 may also estimate the sub-channel matrix from other information instead of a pilot signal. Also, the receiving apparatus 40 feeds back the sub-channel matrix estimated by the channel estimator 44 to the transmitting apparatus 10.
The transmitting apparatus 10 includes a user selector 12, a beamforming matrix calculator 14, a channel encoder 16, a modulation mapping unit 18, a beamforming unit 20, and a plurality of antennas 22. Although four antennas 22 are shown in
The user selector 12 selects a combination of receiving apparatuses 40 in order to simultaneously transmit signals to the receiving apparatuses 40 so that predicted channel capacity, after beamforming, is maximized by using the sub-channel matrix fed back from each receiving apparatus 40. The channel capacity is the maximum speed of a signal that can be transmitted through a channel without an error. Hereinafter, the receiving apparatus 40 may also be referred to as a “user.”
The term “beamforming” in an example embodiment of the present invention refers to a concept where, during communication using a MIMO method, singular vectors calculated from each sub-channel matrix are applied to a transmission symbol vector indicating a transmission signal. Here, a matrix formed by using the singular vectors is a beamforming matrix W. Also, when a channel matrix formed of sub-channel matrices is applied to the result of applying a beamforming matrix W to a transmission symbol vector, a beamforming channel matrix is calculated. In terms of a transmission signal, after beamforming is applied to the transmission signal, a beamforming channel matrix is a new channel matrix in which a beamforming matrix W is applied to a channel matrix.
Referring to Equations 1 through 8 below, a beamforming channel matrix G is obtained by using a channel matrix H and a beamforming matrix W corresponding to a signal that is to be transmitted. Zero-forcing beamforming is beamforming by using singular vectors corresponding to a singular value 0 in regards to each sub-channel matrix.
The beamforming matrix calculator 14 calculates a beamforming matrix W based on the sub-channel matrix fed back from each receiving apparatus 40. For convenience of description, the number of antennas 22 of the transmitting apparatus 10 is four and the number of antennas 42 of each receiving apparatus 40 is two. However, it is understood that more or less than four antennas 22 and two antennas 42 may be used with the transmitting apparatus 10 and the receiving apparatus 40 according to other aspects of the present invention.
Assuming that two receiving apparatuses 40 (users u1 and u2) are selected by the user selector 12, the beamforming matrix calculator 14 generates a MIMO channel matrix H (Equation 3) in regard to a selected user by using sub-channel matrices H1 and H2 of Equations 1 and 2, which are each fed back from the receiving apparatuses 40 of the users u1 and u2.
hij (i=1, 2 j=1, 2, 3, 4) denotes a component indicating a channel characteristic between a j-th antenna of the transmitting apparatus 10 illustrated in
hij (i=3, 4 j=1, 2, 3, 4) denotes a component indicating a channel characteristic between a j-th antenna of the transmitting apparatus 10 of
H denotes a channel matrix wherein a sub-channel matrix between the transmitting apparatus 10 and the receiving apparatus u1 and a sub-channel matrix between the transmitting apparatus and the receiving apparatus u2 are combined. Here, a superscript T is a symbol indicating a transpose matrix.
Then, the beamforming matrix calculator 14 performs singular value decomposition on the sub-channel matrix H2 of the user u2. The singular value decomposition is a method of decomposing a rectangular matrix, wherein a predetermined rectangular matrix is decomposed by using a unitary matrix and a matrix whose diagonal elements are non-negative numbers and whose non-diagonal elements are 0.
Similarly, the beamforming matrix calculator 14 performs singular value decomposition on the sub-channel matrix H1 of the user u1 as shown in Equation 5. Then, the beamforming matrix calculator 14 extracts a plurality of right-singular vectors corresponding to a singular value 0 for each of the sub-channel matrices (H1 and H2). The right-singular vector of the sub-channel matrix H2 corresponding to the singular value 0 is a null space vector 0 of the sub-channel matrix H2. x becomes a null space vector of the sub-channel matrix H2 when H2*x=0. Accordingly, interchannel interference of the receiving apparatus 40 of the user u2 due to a signal of the user u1 can be removed by using a matrix V2(0) formed by the right-singular vector of the sub-channel matrix H2 corresponding to the singular value 0 as a beamforming matrix W of the user u1.
Similarly, the right-singular vector of the sub-channel matrix H1 becomes a null space vector of the sub-channel matrix H1. Accordingly, interchannel interference of the receiving apparatus 40 of the user u1 due to a signal of the user u2 can be removed by using a matrix V1(0) formed by the right-singular vector of the sub-channel matrix H1 corresponding to the singular value 0 as a beamforming matrix W of the user u2.
Here, a superscript H is a symbol for a Hermitian codomain. In the Hermitian codomain, a complex number of a transposed matrix component is substituted by a conjugate complex number.
H2=U2[D20][V2(1)V2(0)]H Equation 4
U2 denotes a unitary matrix corresponding to the sub-channel matrix H2. The unitary matrix denotes a matrix that satisfies U*U=E, where E is a unit matrix. D2 denotes a diagonal matrix that diagonally has singular values obtained by singular value-decomposing the sub-channel matrix H2. The matrix V2(0) is a matrix formed by the right-singular vector of the sub-channel matrix H2 corresponding to the singular value 0. The matrix V2(1) is a matrix formed by the right-singular vector of the sub-channel matrix H2 that corresponds to a singular value excluding 0. Here, a superscript H is a symbol for a Hermitian codomian. For example, when the sub-channel matrix H2 is a 2*4 matrix, U2 is a 2*2 matrix, D2 is a 2*2 matrix, 0 is a 2*2 zero matrix, [D2,0] is a 2*4 matrix, and [V2(1),V2(0)]H is a 4*4 matrix.
H1=U1[D10][V1(1)V1(0)]H Equation 5
U1 denotes a unitary matrix corresponding to the sub-channel matrix H1. D1 denotes a diagonal matrix diagonally having singular values obtained by singular value-decomposing the sub-channel matrix H1. The matrix V1(0) is a matrix formed by a right-singular vector of the sub-channel matrix H1 corresponding to the singular value 0. The matrix V1(1) is a matrix formed by a right-singular vector of the sub-channel matrix H1 corresponding to a singular vector excluding 0.
The beamforming matrix calculator 14 generates a beamforming matrix W by using the matrices V1(0) and V2(0) respectively obtained by singular-value decomposing the sub-channel matrices H1 and H2 as shown in Equation 6. Then, the beamforming matrix calculator 14 transmits the generated beamforming matrix W to the beamforming unit 20.
W=└V2(0),V1(0)┘ Equation 6
Each of the channel encoders 16 encodes data transmitted to a respective receiving apparatus 40 based on a predetermined channel encoding rate. Also, each channel encoder 16 transmits the encoded data to the modulation mapping unit 18. Although four channel encoders 16 are shown in
Each of the modulation mapping unit 18 generates the transmission symbol vector by modulation-mapping the data obtained from a respective channel encoder 16 based on a predetermined modulation order. Then, each modulation mapping unit 18 transmits the generated transmission symbol vector to the beamforming unit 20. Hereinafter, a transmission symbol vector transmitted in regards to the user u1 is denoted as s1=[s11, s12]T and a transmission symbol vector transmitted in regards to the user u2 is denoted as s2=[s21, s22]T. Although four modulation mapping units 18 are shown in
The beamforming unit 20 generates a transmission symbol vector after the beamforming by adding up the transmission symbol vectors for each user obtained from the modulation mapping units 18 and the beamforming matrix W generated by the beamforming matrix calculator 14. When the transmission symbol vectors s1 and s2 of the users u1 and u2 are added up and denoted as s=[s1T, s2T]T, a reception signal vector (r=[r1T, r2T]T) can be expressed as a multiplication of the channel matrix H, the beamforming matrix W, and the transmission symbol vector s as shown in Equation 7. Also, since the beamforming matrix W is generated as shown in Equation 6, an interference component between users is 0 as shown in Equation 7. Here, r1=[r11, r12]T and r2=[r21, r22]T.
As described above, the transmitting apparatus 10 calculates the beamforming matrix W by using the null space vector obtained by singular value-decomposing the sub-channel matrix fed back from each receiving apparatus 40, and transmits the beamforming matrix W after adding the beamforming matrix W with the transmission symbol vector s. Accordingly, the beamforming matrix W can be transmitted in such a way that the beamforming matrix W does not interfere with the users. This is conceptually illustrated in
The receiving apparatus selector 310 selects a combination of receiving apparatuses 40 (
The beamforming matrix calculator 320 calculates a beamforming matrix W based on the channel matrix. The beamforming channel matrix calculator 330 calculates a beamforming channel matrix which shows a channel characteristic after beamforming between the transmitting apparatus 301 and one of the receiving apparatuses 40. The beamforming channel matrix is a matrix that shows a channel characteristic when a signal is transmitted from the transmitting apparatus 301 to one of the receiving apparatuses 40 after beamforming the signal. The beamforming channel matrix calculator 330 calculates the beamforming channel matrix based on the beamforming matrix W calculated by the beamforming matrix calculator 320 and the channel matrix fed back from each receiving apparatus 40. The beamforming channel matrix calculator 330 performs singular value decomposition on the channel matrix that shows a channel characteristic between the transmitting apparatus 301 and one of the receiving apparatuses 40, and calculates the beamforming channel matrix by using the beamforming matrix W, which includes a null space vector corresponding to a singular value 0 obtained as a result of the singular value decomposition, and the channel matrix. The beamforming channel matrix calculated by the beamforming matrix calculator 320 is block-diagonalized according to each channel as shown in Equation 7.
The error rate estimator 340 estimates an error rate that occurs while transmitting the signal after the beamforming, by using the beamforming channel matrix calculated by the beamforming channel matrix calculator 330. The error rate estimator 340 estimates the error rate by using noise information, which is included while transmitting the signal after the beamforming, and received power, which is estimated from the beamforming channel matrix. According to an aspect of the present invention, the error rate is a signal power to interference plus noise power ratio (SINR), although it is understood that the error rate is not limited to being an SINR and may instead be other types of error rates known in the art. The error rate estimator 340 estimates the error rate based on SINR at each sub-stream corresponding to each block of the block-diagonalized beamforming channel matrix. The error rate estimator 340 calculates the minimum Euclid distance at each selectable modulation order of each block of the block-diagonalized beamforming channel matrix, and calculates SINR at each sub-stream based on the result of calculating the minimum Euclid distance.
The transmission parameter selector 350 selects parameters used while transmitting the signal so that the error rate is below a predetermined value. According to an aspect of the present invention, the parameters include a channel encoding rate used while channel-encoding a transmission signal and a modulation order used while modulation-mapping the transmission signal. It is understood that the channel encoding rate and the modulation order may be used individually or in combination, and that other aspects of the present invention may use different parameters altogether. The transmission parameter selector 350 sets up a transmission rate between the transmitting apparatus 301 and one of the receiving apparatuses by using the selected parameters. Examples of such parameters include a channel encoding rate, a modulation order, etc.
The transmitter 360 transmits a data signal by using the parameters selected by the transmission parameter selector 350. The transmitter 360 may transmit the data signal wirelessly, through a wired connection, or through a combination of both wireless and wired connections.
In operation 410, the transmitting apparatus 301 calculates a beamforming matrix W based on channel matrices that show channel characteristics between the transmitting apparatus 301 and a plurality of receiving apparatuses 40. In operation 420, the transmitting apparatus W calculates a beamforming channel matrix based on the beamforming matrix W calculated in operation 410 and channel matrices received from the receiving apparatuses 40.
In operation 430, the transmitting apparatus 301 estimates an error rate that occurs while the receiving apparatus 40 receives a signal, by using the beamforming channel matrix calculated in operation 420 and noise information received from the receiving apparatus 40. In operation 440, the transmitting apparatus 301 selects parameters used to transmit a data signal to the receiving apparatus 40 according to the error rate estimated in operation 430.
In operation 450, the transmitting apparatus 301 transmits the data signal by using the parameters selected in operation 440.
As illustrated in
As illustrated in
The channel estimator 154 estimates a sub-channel matrix that shows a transmission characteristic of a sub-channel between the transmitting apparatus 100 and the receiving apparatus 150. For example, the channel estimator 154 may estimate a sub-channel matrix by using a pilot signal added to a transmission signal by the transmitting apparatus 100, although it is understood that the channel estimator 154 may instead use other types of information to estimate a sub-channel matrix according to other aspects of the present invention. The receiving apparatus 150 transmits the estimated sub-channel matrix to the transmitting apparatus 100.
The noise variance estimator 156 estimates a noise variance value (or a noise power value) by using the pilot signal. Then, the receiving apparatus 150 transmits the estimated noise variance value to the transmitting apparatus 100.
The beamforming channel estimator 158 estimates a sub-channel matrix of the transmission signal on which beamforming is performed. A reception signal vector r is obtained by multiplying a transmission symbol vector s by a result HW of multiplying a channel matrix H and a beamforming matrix W as expressed in Equation 7. Also, a channel matrix (G=HW), which is generated after the beamforming estimated by the sub-channel matrix, is block-diagonalized at each sub-channel as shown in Equation 7 or 8. For example, in the case of the receiving apparatus 150 of a user u1, the beamforming channel estimator 158 estimates a sub-channel matrix G1 which is included in the channel matrix G after the beamforming and corresponds to the user u1. The beamforming channel estimator 158 transmits the estimated sub-channel matrix G1 to the maximum likelihood detector 160.
The maximum likelihood detector 160 separates a reception signal by using information, such as information on the modulation order, notified by the transmitting apparatus 100, and the sub-channel matrix after the beamforming estimated by the beamforming channel estimator 158, and detects a transmission symbol transmitted to the receiving apparatus 150. According to an aspect of the present invention, the maximum likelihood detector 160 uses a maximum likelihood detection (MLD) method, which has superior transmission characteristics compared to a minimum mean square error (MMSE) detection method, as a signal separation algorithm. It is understood, however, that the maximum likelihood detector 160 is not limited to using the MLD method, and may instead use various other types of detection methods, including the MMSE method. Also, the maximum likelihood detector 160 transmits the transmission symbol detected at each sub-stream to the channel decoder 162.
The channel decoder 162 decodes the original data by performing decoding of error correction based on information, such as information on a channel encoding rate, notified by the transmitting apparatus 100. It is understood that the channel decoder 162 may also use other parameters, such as a modulation order, instead of or in addition to a channel encoding rate, to decode the original data.
As illustrated in
The user selector 102 selects a combination of receiving apparatuses 150 to which the user selector 102 will simultaneously transmit a signal, so that estimated channel capacity after the beamforming is maximized by using sub-channel matrices H1 and H2 fed back from each of the receiving apparatuses 150. The user selector 102 transmits information about the combination of the selected receiving apparatuses 150 to the beamforming matrix calculator 104. Also, for convenience of description, the receiving apparatuses 150 of users u1 and u2 are selected. However, the transmitting apparatus 100 is not limited thereto, and may instead transmit a signal to more or less than the two users u1 and u2.
The beamforming matrix calculator 104 calculates a beamforming matrix W which enables data signals to be transmitted to the receiving apparatuses 150 without interfering with each other by using the sub-channel matrices H1 and H2 fed back from the receiving apparatuses 150 selected by the user selector 102.
In detail, the beamforming matrix calculator 104 singular value-decomposes the sub-channel matrix H2 of the user u2 as shown in Equation 4. Similarly, the beamforming matrix calculator 104 singular value-decomposes the sub-channel matrix H1 of the user u1 as shown in Equation 5. Also, the beamforming matrix calculator 104 extracts a plurality of right-singular vectors corresponding to a singular value 0 in regard to each of the sub-channel matrices H1 and H2. Also, as shown in Equation 6, the beamforming matrix calculator 104 generates a beamforming matrix W by using matrices V1(0) and V2(0) obtained by singular value-decomposing each of the sub-channel matrices H1 and H2.
Then, the beamforming matrix calculator 104 transmits the generated beamforming matrix W to the beamforming unit 116 and simultaneously transmits the matrices V1(0) and V2(0) formed by the right-singular vector corresponding to the singular value 0 to the beamforming channel matrix calculator 106. For example, the beamforming matrix calculator 104 transmits the matrix V2(0) to the beamforming channel matrix calculator 106, which calculates the beamforming channel matrix G1 corresponding to the user u1.
The beamforming channel matrix calculator 106 calculates an assumed beamforming channel matrix G by adding up the beamforming matrix W obtained from the beamforming matrix calculator 104 and the channel matrix H in regard to the combination selected by the user selector 102. Here, when a beamforming channel matrix G2 corresponding to the sub-channel matrix H2 is calculated, one of the beamforming channel matrix calculators 106 calculates the beamforming channel matrix G2 by using the matrix V1(0) obtained from the beamforming matrix calculator 104 and the sub-channel matrix H2 obtained from the receiving apparatus 150 of the user u2. The beamforming channel matrix G1 is calculated in a similar manner. The sub-matrices G1 and G2 of the beamforming channel matrix G are equivalent channel matrices of the receiving apparatuses 150 of the selected users u1 and u2. In other words, the sub-matrices G1 and G2 of the beamforming channel matrix G become channel matrices of each receiving apparatus 150 after the beamforming.
The reception SINR estimators 108 calculate reception powers by using the respective beamforming channel matrices G1 and G2 obtained from the beamforming channel matrix calculators 106. Also, the reception SINR estimators 108 estimate SINRs detected from the receiving apparatus 150 by using the noise variance value (or noise power) fed back from the receiving apparatus 150 and the reception power calculated from the beamforming channel matrices G1 and G2. Then, the reception SINR estimators 108 transmit information about the estimated SINRs for the respective beamforming channel matrices G1 and G2 to corresponding MCS selectors 110. For example, one of the reception SINR estimator 108 may estimate the average SINR detected from the receiving apparatus 150 of the user u2 by using the beamforming channel matrix G2 and the noise variance value Pn2 fed back from the receiving apparatus 150 of the user u2. It is understood, however, that the reception SINR estimator 108 is not limited to using the noise variance value Pn2 fed back from the receiving apparatus 150 of the user u2, and may instead use other values instead of or in addition to the noise variance value Pn2.
The MCS selectors 110 respectively determine an MCS (modulating and coding set) based on the estimated SINR of each receiving apparatus 150 obtained from the respective reception SINR estimators 108. For example, one of the MCS selectors 110 selects a channel encoding rate and modulation order of an error correction code in which the error rate is below a predetermined value and the transmission speed is the maximum. Then, the MCS selector 110 transmits information about the selected channel encoding rate to the channel encoder 112, and simultaneously transmits information about the selected modulation order to the modulation mapping unit 114.
Each of the channel encoders 112 encodes data based on the channel encoding rate selected by the corresponding MCS selector 110. Then, the channel encoder 112 transmits the encoded data to the modulation mapping unit 114. Although
Each of the modulation mapping units 114 modulation-maps a respective group of the encoded data based on the selected modulation order. Also, each of the modulation mapping units 114 transmits a transmission symbol obtained by modulation-mapping the respective groups of encoded data to the beamforming unit 116. For example, data d2 transmitted to the receiving apparatus 150 of the user u2 is converted in series and in parallel, encoded by the channel encoder 112, modulation-mapped by the modulation mapping unit 114, and then converted as a transmission symbol vector (s2=[s21, s22]) to the user u2. Also, a user indicated by a control signal included in a transmission signal format, is notified about the information on the selected modulation order and channel encoding rate.
The beamforming unit 116 generates a transmission symbol vector s′ after the beamforming by adding up each of the transmission symbol vectors s1 and s2 obtained from the modulation mapping unit 114 and the beamforming matrix W generated by the beamforming matrix calculator 104. Also, the beamforming unit 116 transmits the transmission symbol vector s′ to the receiving apparatus 150 through each antenna 118.
The communication system 1000 has been described above. According to the communication system 1000, a sub-channel matrix of each receiving apparatus 150 is calculated in the transmitting apparatus 100. Thus, the SINR detected in the receiving apparatus 150 is estimated based on each sub-channel matrix. As a result, the transmitting apparatus 100 transmits a suitable error correction encoding rate and modulation order based on the estimated SINR, thereby obtaining a stable throughput, i.e., data transfer rate, without depending on channel circumstances. Also, since most of the processes of setting up a transmission rate are performed in the transmitting apparatus 100, power consumed by the receiving apparatus 150 is reduced. In addition, a transmission control parameter, such as an encoding rate or a modulation order, is transmitted to the receiving apparatus 150 by being included in a transmission signal.
As illustrated in
As illustrated in
Each one of the SINR estimators which estimate respective SINRs after a MLD estimation operation is performed for each sub-stream 208 (hereinafter, referred to as the SINR estimators 208) obtains sub-channel matrices G1 and G2 after a beamforming operation is calculated by the beamforming channel matrix calculator 106, and calculates the minimum Euclid distance at each predetermined modulation order in regard to the sub-channel matrices G1 and G2.
However, it is difficult to estimate the minimum Euclid distance for each sub-stream, and various methods may be used. For example, in one exemplary method, a differential modulation symbol, which is a difference between two different modulation symbols, is calculated in regard to all modulation signal points included in a signal point arrangement of a predetermined modulation method, and a Euclid distance is calculated in regard to each of various differential modulation symbol vectors formed of a combination of differential modulation symbols. Then, a differential modulation symbol vector, wherein the Euclid distance is at a minimum, should be selected from among differential modulation symbol vectors in which the differential modulation symbol corresponding to each sub-stream is not 0. The Euclid distance corresponding to such a differential modulation symbol vector is the minimum Euclid distance.
For example, when a modulation multinary number is M and the number of transmission antennas is NT, the combined number of differential modulation symbol vectors is M^(NT). Accordingly, when the number of transmission antennas is 4 and a modulation method is 16 QAM (16 quadrature amplitude modulation), a Euclid distance should be calculated in regard to the combination, such as 494=5,764,801, in order to obtain the minimum Euclid distance. As described above, the amount of calculations used to calculate the minimum Euclid distance is massive, and thus such a method is not regarded as being a realistic option.
A solution for such a problem has been developed by the applicant of the present invention, and is disclosed in a patent which the applicant has applied for in the Japanese Patent Office (Japanese patent application no. 2006-282376). Here, the applicant suggests a Trellis search algorithm, where a channel matrix is decomposed (QR decomposition) by a unitary matrix and an upper triangular matrix, a candidate for a differential modulation symbol vector is selected so that a Euclid distance corresponding to each row vector of the upper triangular matrix is small, and a differential modulation symbol is extracted so that the corresponding Euclid distance in a predetermined condition is at a minimum. A Euclid distance corresponding to the differential modulation symbol extracted based on the Trellis search algorithm is the desired minimum Euclid distance. By using the Trellis search algorithm, it is possible to achieve a high speed of approximately 22,500 times faster than a conventional search algorithm, when the number of transmission antennas is 4 and the modulation method is 16 QAM. Accordingly, it becomes a realistic option to calculate the minimum Euclid distance at each sub-stream.
Each of the SINR estimators 208 calculates the minimum Euclid distance for a respective sub-stream by using the Trellis search algorithm in regard to the sub-channel matrices G1 and G2 after the beamforming. Then, each one of the SINR estimators 208 calculates an SINR for a respective sub-stream in regard to the candidate of the predetermined modulation method by using the minimum Euclid distance calculated for the respective sub-stream and the noise variance value fed back from the receiving apparatus 150 of a respective user. Also, the SINR estimators 208 transmit the SINRs of the respective sub-streams to a corresponding one of the MCS selectors located at each sub-stream 210.
The MCS selector at each sub-stream 210 (hereinafter referred to as the “MCS selector 210”) predicts a bit error rate or packet error rate after performing an MLD operation and error correction decoding based on the SINR of each sub-stream calculated by the respective SINR estimator 208, and selects an encoding rate and modulation order for each sub-stream in such a way that when the predicted bit error rate or packet error rate is below a predetermined value, the transmission speed is high. Also, the MCS selector 210 transmits the selected encoding rate to the channel encoder 112 and simultaneously transmits the selected modulation order to the modulation mapping unit 114.
Also, the transmitting apparatus 200 notifies the receiving apparatus 150 about information on the selected encoding rate and the modulation order by recording the information in a control signal of a transmission signal format. Then, the MCS selector 210 may select an encoding rate and modulation order of each sub-stream or a common encoding rate and modulation order of the sub-streams. In the former case, one of the channel encoders 112 and one of the modulation mapping units 114 respectively perform the channel encoding and the modulation mapping on a respective sub-stream by using the encoding rate and the modulation order selected by the MCS selector 210. In the latter case, one of the channel encoders 112 and one of the modulation mapping units 114 respectively perform the channel encoding and the modulation mapping on the whole sub-stream by using the encoding rate and the modulation order selected by the MCS selector 210.
The communication system 2000 has been described above. By using the communication system 2000, the transmitting apparatus 200 calculates the sub-channel matrix in regard to each receiving apparatus 150, thereby making it possible to estimate the minimum Euclid distance of each sub-stream detected by the receiving apparatus 150 from each sub-channel matrix. As a result, the transmitting apparatus 200 selects the encoding rate and the modulation order based on the SINR estimated at each sub-stream. Accordingly, stable throughput is obtained without depending on channel conditions. Also, since a transmission control parameter is selected at each sub-channel, more suitable transmission control is possible in regard to the MLD performed by the receiving apparatus 150 in comparison with the receiving apparatus 150 of the communication system 1000. Accordingly, the MLD detection method, which obtains better transmission characteristics than the MMSE detection method, can be applied in the communication system 2000. Moreover, transmission control suitable for the MLD is realized.
The beamforming channel estimator 710 receives a pilot signal in which beamforming is applied, and calculates a beamforming channel matrix by using the received pilot signal.
The error rate estimator 720 estimates an error rate while transmitting a signal after the beamforming, based on the calculated beamforming channel matrix. The error rate estimator 720 estimates the error rate by using noise information included in the signal after the beamforming and the calculated beamforming channel matrix. The error rate estimator 720 estimates the error rate based on an SINR corresponding to each block of a block-diagonalized beamforming channel matrix. The error rate estimator 720 calculates the minimum Euclid distance at each selectable modulation order of each block of the block-diagonalized beamforming channel matrix, and calculates the SINR of each sub-stream based on the result of calculating the minimum Euclid distance.
The transmission parameter selector 730 selects parameters, which enable the error rate to drop below a predetermined value. According to an aspect of the present invention, the parameters are a channel encoding rate, which is used to channel-encode a transmission signal, and a modulation order, which is used to modulation-map the transmission signal.
The transmitter 740 transmits the selected parameters to a transmitting apparatus which transmitted the pilot signal. According to an aspect of the present invention, the transmitting apparatus is one of the transmitting apparatuses 301, 100, or 200, shown in
In operation 810, the receiving apparatus 701 using beamforming receives a pilot signal from a transmitting apparatus 301 (
In operation 820, the receiving apparatus 701 estimates a beamforming channel matrix based on the received pilot signal. It is understood, however, that the receiving apparatus 701 is not limited to estimating a beamforming channel matrix based on a received pilot signal in all aspects of the present invention, and may use other types of information instead of or in addition to the received pilot signal.
In operation 830, the receiving apparatus 701 estimates an error rate while the receiving apparatus 701 receives the pilot signal by using the beamforming channel matrix estimated in operation 820 and noise information included in the received pilot signal.
In operation 840, the receiving apparatus 701 selects parameters used while transmitting a data signal, according to the error rate estimated in operation 830.
In operation 850, the receiving apparatus 701 transmits the parameters selected in operation 840 to the transmitting apparatus 301.
The communication system 3000 will now be described in detail with reference to
The transmitting apparatus 300 includes a user selector 102, a beamforming matrix calculator 104, a plurality of channel encoders 112, a plurality of modulation mapping units 114, a pilot signal includer for beamforming channel estimation 302, a beamforming unit 116, and a plurality of antennas 118.
The pilot signal includer for beamforming channel estimation 302 (hereinafter, referred to as the “pilot signal includer 302”) adds a pilot signal to a transmission symbol vector inputted from the modulation mapping unit 114 to estimate a sub-channel matrix after beamforming. Also, the pilot signal includer 302 transmits the transmission symbol vector including the pilot signal to the beamforming unit 116.
The beamforming unit 116 performs the beamforming on the transmission symbol vector including the pilot signal based on the calculated beamforming matrix W and then transmits the transmission symbol vector.
The channel encoders 112 and the modulation mapping units 114 respectively perform channel encoding and modulation mapping based on information about the encoding rate and the modulation order fed back from the receiving apparatus 350.
As illustrated in
The reception SINR estimator 352 calculates a reception power by using a sub-channel matrix G1 after the beamforming estimated by the beamforming channel estimator 158. The reception SINR estimator 352 estimates a reception SINR after the beamforming by using the estimated noise variance value and the calculated reception power. Then, the reception SINR estimator 352 transmits information about the estimated reception SINR to the MCS selector 354.
The MCS selector 354 determines a transmission control parameter MCS1 based on an estimated value of the reception SINR. For example, the MCS selector 354 selects a channel encoding rate and a modulation order of an error correction code so that the error rate is below a predetermined value while the transmission speed is maximized. The MCS selector 354 transmits information about the selected channel encoding rate to the channel encoders 112 and simultaneously transmits information about the selected modulation order to the modulation mapping units 114. The channel encoding rate and the modulation order are used in the maximum likelihood detector 160 or the channel decoder 162.
The communication system 3000 has been described above. In the communication system 3000, the transmitting apparatus 350 estimates a sub-channel matrix by transmitting the pilot signal after the beamforming. Also, the error correction encoding rate and the modulation order suitable for the receiving apparatus 350 are selected based on the reception SINR estimated from the sub-channel matrix. Also, since the parameters are set up based on the signal obtained through a channel which is actually used, the transmission control parameters are selected with a higher precision than by the communication system 1000.
The communication system 4000 will now be described in detail with reference to
As illustrated in
The SINR estimator after MLD at each sub-stream 452 (hereinafter, referred to as the “SINR estimator 452”) first obtains a sub-channel matrix G1 after the beamforming estimated by the beamforming channel estimator 158, and then calculates the minimum Euclid distance according to a predetermined modulation method in regards to the sub-channel matrix G1. As described above, it is difficult to estimate the minimum Euclid distance for each sub-stream. Thus, the SINR estimator 452 uses the same Trellis search algorithm as the SINR estimator 208 of the communication system 2000 (
The SINR estimator 452 calculates the SINR of each sub-stream after the MLD operation in regard to a candidate of the predetermined modulation method by using the calculated minimum Euclid distance and the estimated noise variance value. Then, the SINR estimator 452 transmits the calculated SINR of each sub-stream to the MCS selector in each sub-stream 454.
The MCS selector at each sub-stream 454 (hereinafter, referred to as the “MCS selector 452”) predicts a bit error rate or packet error rate after performing an MLD operation and error correction decoding based on the SINR of each sub-stream after the MLD calculated by the SINR estimator 452, and selects an encoding rate and modulation order that decreases the predicted bit error rate or packet error rate below a predetermined value while increasing the transmission speed. Also, the MCS selector 454 transmits the selected encoding rate to the channel encoders 112 and simultaneously transmits the selected modulation order to the modulation mapping units 114.
The communication system 4000 has been described above. According to the communication system 4000, the receiving apparatus 450 estimates the sub-channel matrix by transmitting the pilot signal after performing the beamforming. Also, the error correction encoding rate and modulation order suitable for the receiving apparatus 450 are selected based on the reception SINR estimated from the sub-channel matrix. Also, since a transmission rate is set up based on the signal obtained through a channel which is actually used, the transmission control parameter is selected with a higher precision than by the communication system 1000. Moreover, it is possible to select the transmission control parameter for each sub-stream based on the SINR of each sub-stream after the MLD, to thereby control the transmission rate in a more suitable fashion for the MLD operation than by the communication system 3000.
As described above, in a multi-user MIMO system using zero-forcing beamforming according to aspects of the present invention, it is possible to set up a suitable transmission rate even when a receiving apparatus uses MLD. As a result, communication quality becomes stable and throughput increases.
In the embodiments of the present invention described above, a transmitting method and a receiving method for transmitting and receiving apparatuses of a certain user, such as the user u1, has been described for convenience of description. However, the transmitting or receiving method can be applied to a transmitting or receiving apparatus of two or more other users in addition to the user u1. The characteristics of each embodiment of the present invention can be combined. Also, the transmitting apparatus may include a receiving function, and the receiving apparatus may include a transmitting function. Alternatively, structures of the transmitting apparatus and the receiving apparatus may be included in one communication apparatus. In addition, the transmitting apparatus may further include a notification means to notify the receiving apparatus about information, and the receiving apparatus may further include a feedback means to feed back information to the transmitting apparatus. Also, the receiving and/or transmitting apparatuses can be employed in various computer networks, such as local area networks (LANs), the Internet, etc.
In addition to the above described embodiments, embodiments of the present invention can also be implemented through computer readable code/instructions in/on a medium, e.g., a computer readable medium, to control at least one processing element to implement any above described embodiment. The medium can correspond to any medium/media permitting the storing and/or transmission of the computer readable code.
The computer readable code can be recorded/transferred on a medium in a variety of ways, with examples of the medium including recording media, such as magnetic storage media (e.g., ROM, floppy disks, hard disks, etc.) and optical recording media (e.g., CD-ROMs, or DVDs), for example. The media may also be a distributed network, so that the computer readable code is stored/transferred and executed in a distributed fashion. Still further, as only an example, the processing element could include a processor or a computer processor, and processing elements may be distributed and/or included in a single device.
While aspects of the present invention has been particularly shown and described with reference to differing embodiments thereof, it should be understood that these exemplary embodiments should be considered in a descriptive sense only and not for purposes of limitation. Any narrowing or broadening of functionality or capability of an aspect in one embodiment should not considered as a respective broadening or narrowing of similar features in a different embodiment, i.e., descriptions of features or aspects within each embodiment should typically be considered as available for other similar features or aspects in the remaining embodiments.
Thus, although a few embodiments of the present invention have been shown and described, it would be appreciated by those skilled in the art that changes may be made in this embodiment without departing from the principles and spirit of the invention, the scope of which is defined in the claims and their equivalents.
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